Sensor instruments and systems are deployed in a variety of consumer, industrial, and commercial applications. As an example of sensor deployment in a common industrial setting, tank farms and tank terminals provide a series of storage tanks containing various products (e.g. petrochemicals) that pass through different stages of a processing workflow. High accuracy and reliability of field instruments (e.g. level sensors and temperature sensors) is needed for precise volume calculations in these storage tanks. However, field instruments may, under certain conditions, generate invalid data, such as data jumps, out-of-range data, excessive variance (noise), frozen readings, missing data, and the like. Invalid sensor readings may pose a safety issue and may also cause financial losses if undetected.
Invalid or inaccurate sensor data may be caused by a variety of factors, including: sensor fault (mechanical or electrical) initiated by various damage mechanisms (e.g. water ingress), power outages, communication errors, incorrect value of instrument parameters, and the like. Although some field instruments may already be equipped with some level of on-board diagnostic functionality, the existing diagnostic algorithms deployed in sensors and in sensor monitoring systems may not be able to detect all cases of invalid data.